v3-memory-unification

# V3 Memory Unification ## What This Skill Does Consolidates disparate memory systems into unified AgentDB backend with HNSW vector search, achieving 150x-12,500x search performance improvements while maintaining backward compatibility. ## Quick Start ```bash # Initialize memory unification Task("Memory architecture", "Design AgentDB unification strategy", "v3-memory-specialist") # AgentDB integration Task("AgentDB setup", "Configure HNSW indexing and vector search", "v3-memory-specialist") # Data migration Task("Memory migration", "Migrate SQLite/Markdown to AgentDB", "v3-memory-specialist") ``` ## Systems to Unify ### Legacy Systems → AgentDB ``` ┌─────────────────────────────────────────┐ │ • MemoryManager (basic operations) │ │ • DistributedMemorySystem (clustering) │ │ • SwarmMemory (agent-specific) │ │ • AdvancedMemoryManager (features) │ │ • SQLiteBackend (structured) │ │ • MarkdownBackend (file-based) │ │ • HybridBackend (combination) │ └─────────────────────────────────────────┘ ↓ ┌─────────────────────────────────────────┐ │ 🚀 AgentDB with HNSW │ │ • 150x-12,500x faster search │ │ • Unified query interface │ │ • Cross-agent memory sharing │ │ • SONA learning integration │ └─────────────────────────────────────────┘ ``` ## Implementation Architecture ### Unified Memory Service ```typescript class UnifiedMemoryService implements IMemoryBackend { constructor( private agentdb: AgentDBAdapter, private indexer: HNSWIndexer, private migrator: DataMigrator, ) {} async store(entry: MemoryEntry): Promise<void> { await this.agentdb.store(entry); await this.indexer.index(entry); } async query(query: MemoryQuery): Promise<MemoryEntry[]> { if (query.semantic) { return this.indexer.search(query); // 150x-12,500x faster } return this.agentdb.query(query); } } ``` ### HNSW Vector Search ```typescript class HNSWIndexer { constructor(dimensions: number = 1536) { this.index = new HNSWIndex({ dimensions, efConstruction: 200, M: 16, speedupTarget: "150x-12500x", }); } async search(query: MemoryQuery): Promise<MemoryEntry[]> { const embedding = await this.embedContent(query.content); const results = this.index.search(embedding, query.limit || 10); return this.retrieveEntries(results); } } ``` ## Migration Strategy ### Phase 1: Foundation ```typescript // AgentDB adapter setup const agentdb = new AgentDBAdapter({ dimensions: 1536, indexType: "HNSW", speedupTarget: "150x-12500x", }); ``` ### Phase 2: Data Migration ```typescript // SQLite → AgentDB const migrateFromSQLite = async () => { const entries = await sqlite.getAll(); for (const entry of entries) { const embedding = await generateEmbedding(entry.content); await agentdb.store({ ...entry, embedding }); } }; // Markdown → AgentDB const migrateFromMarkdown = async () => { const files = await glob("**/*.md"); for (const file of files) { const content = await fs.readFile(file, "utf-8"); await agentdb.store({ id: generateId(), content, embedding: await generateEmbedding(content), metadata: { originalFile: file }, }); } }; ``` ## SONA Integration ### Learning Pattern Storage ```typescript class SONAMemoryIntegration { async storePattern(pattern: LearningPattern): Promise<void> { await this.memory.store({ id: pattern.id, content: pattern.data, metadata: { sonaMode: pattern.mode, reward: pattern.reward, adaptationTime: pattern.adaptationTime, }, embedding: await this.generateEmbedding(pattern.data), }); } async retrieveSimilarPatterns(query: string): Promise<LearningPattern[]> { return this.memory.query({ type: "semantic", content: query, filters: { type: "learning_pattern" }, }); } } ``` ## Performance Targets - **Search Speed**: 150x-12,500x improvement via HNSW - **Memory Usage**: 50-75% reduction through optimization - **Query Latency**: <100ms for 1M+ entries - **Cross-Agent Sharing**: Real-time memory synchronization - **SONA Integration**: <0.05ms adaptation time ## Success Metrics - [ ] All 7 legacy memory systems migrated to AgentDB - [ ] 150x-12,500x search performance validated - [ ] 50-75% memory usage reduction achieved - [ ] Backward compatibility maintained - [ ] SONA learning patterns integrated - [ ] Cross-agent memory sharing operational